Publications
Analytical models and methods for anomaly detection in dynamic, attributed graphs
Summary
Summary
This chapter is devoted to anomaly detection in dynamic, attributed graphs. There has been a great deal of research on anomaly detection in graphs over the last decade, with a variety of methods proposed. This chapter discusses recent methods for anomaly detection in graphs,with a specific focus on detection within...
Cross-domain entity resolution in social media
Summary
Summary
The challenge of associating entities across multiple domains is a key problem in social media understanding. Successful cross-domain entity resolution provides integration of information from multiple sites to create a complete picture of user and community activities, characteristics, and trends. In this work, we examine the problem of entity resolution...
Charting a security landscape in the clouds: data protection and collaboration in cloud storage
Summary
Summary
This report surveys different approaches to securely storing and sharing data in the cloud based on traditional notions of security: confidentiality, integrity, and availability, with the main focus on confidentiality. An appendix discusses the related notion of how users can securely authenticate to cloud providers. We propose a metric for...
Balancing security and performance for agility in dynamic threat environments
Summary
Summary
In cyber security, achieving the desired balance between system security and system performance in dynamic threat environments is a long-standing open challenge for cyber defenders. Typically an increase in system security comes at the price of decreased system performance, and vice versa, easily resulting in systems that are misaligned to...
Collaborative Data Analysis and Discovery for Cyber Security
Summary
Summary
In this paper, we present the Cyber Analyst Real-Time Integrated Notebook Application (CARINA). CARINA is a collaborative investigation system that aids in decision making by co-locating the analysis environment with centralized cyber data sources, and providing next generation analysts with increased visibility to the work of others.
Channel compensation for speaker recognition using MAP adapted PLDA and denoising DNNs
Summary
Summary
Over several decades, speaker recognition performance has steadily improved for applications using telephone speech. A big part of this improvement has been the availability of large quantities of speaker-labeled data from telephone recordings. For new data applications, such as audio from room microphones, we would like to effectively use existing...
The MITLL NIST LRE 2015 Language Recognition System
Summary
Summary
In this paper we describe the most recent MIT Lincoln Laboratory language recognition system developed for the NIST 2015 Language Recognition Evaluation (LRE). The submission features a fusion of five core classifiers, with most systems developed in the context of an i-vector framework. The 2015 evaluation presented new paradigms. First...
A vocal modulation model with application to predicting depression severity
Summary
Summary
Speech provides a potential simple and noninvasive "on-body" means to identify and monitor neurological diseases. Here we develop a model for a class of vocal biomarkers exploiting modulations in speech, focusing on Major Depressive Disorder (MDD) as an application area. Two model components contribute to the envelope of the speech...
BubbleNet: A Cyber Security Dashboard for Visualizing Patterns
Summary
Summary
The field of cyber security is faced with ever-expanding amounts of data and a constant barrage of cyber attacks. Within this space, we have designed BubbleNet as a cyber security dashboard to help network analysts identify and summarize patterns within the data.
Operational assessment of keyword search on oral history
Summary
Summary
This project assesses the resources necessary to make oral history searchable by means of automatic speech recognition (ASR). There are many inherent challenges in applying ASR to conversational speech: smaller training set sizes and varying demographics, among others. We assess the impact of dataset size, word error rate and term-weighted...